Smoldering multiple myeloma (SMM) is a precursor stage that precedes multiple myeloma (MM). SMM is heterogenous with nearly 40% of patients progressing to MM in the first 5 years. The high rate of progression of SMM patients highlights the need for early intervention, which underscores the importance of identifying SMM patients with the highest risk of progression. Several risk stratification models showed utility in identifying high-risk SMM patients; however, these systems showed limited sensitivity. To date, identifying high-risk SMM patients remains an important clinical need. In this study, we present the 3-dimensional telomere profiling as a structural biomarker capable of stratifying SMM patients as a function of genomic instability. Quantifying telomere dysfunction using the TeloView technology showed utility in risk stratification of cancer patients, particularly hematological malignancies. In this study, we analyzed 168 SMM patients. We report an AUC in ROC analysis of 0.8 using a subset of the patients as a training dataset. We then conducted a blind validation on a different cohort and demonstrated a positive predictive value of 85% and negative predictive value of 73%, with sensitivity and specificity of 83% and 76%, respectively. We examined the correlation between the TeloView prediction and the 20-2-20 scoring system, and cytogenetic abnormalities. We report a correlation of 53% with the 20-2-20 scores and over 60% correlation with cytogenetic abnormalities. The result of this study presents the telomere profiling as an effective biomarker able to stratify SMM patients to their respective risk groups with high sensitivity and specificity.
© 2024 The Authors. American Journal of Hematology published by Wiley Periodicals LLC.